/C-VFL

Compressed Vertical Federated Learning simulation code

Primary LanguagePython

Compressed Vertical Federated Learning

Code for simulating C-VFL, a communication-efficient algorithm for vertically partitioned data. More details on the algorithm can be in our paper: Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data:

@inproceedings{castiglia2022compressed,
  title={Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data},
  author={Castiglia, Timothy and Das, Anirban and Wang, Shiqiang and Patterson, Stacy},
  booktitle={International Conference on Machine Learning},
  year={2022}
}

Dependencies

One can install our environment with Anaconda:

conda env create -f flearn.yml

Repository Structure

'ModelNet_CVFL': contains code for running C-VFL with the ModelNet10 and CIFAR-10 datasets

'ImageNet_CVFL': contains code for running C-VFL with the ImageNet dataset

'mimic3_CVFL': contains code for running C-VFL with the MIMIC-III dataset

Information on how to run C-VFL are provided in the README's in each folder.